Search

Background Suppression of background parenchymal enhancement (BPE) is commonly observed after neoadjuvant chemotherapy (NAC) at contrast-enhanced breast MRI. It was hypothesized that nonsuppressed BPE may be associated with inferior response to NAC. Purpose To investigate the relationship between lack of BPE suppression and pathologic response. Materials and Methods A retrospective review was performed for women with menopausal status data who were treated for breast cancer by one of 10 drug arms (standard NAC with or without experimental agents) between May 2010 and November 2016 in the Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2, or I-SPY 2 TRIAL (NCT01042379). Patients underwent MRI at four points: before treatment (T0), early treatment (T1), interregimen (T2), and before surgery (T3). BPE was quantitatively measured by using automated fibroglandular tissue segmentation. To test the hypothesis effectively, a subset of examinations with BPE with high-quality segmentation was selected. BPE change from T0 was defined as suppressed or nonsuppressed for each point. The Fisher exact test and the Z tests of proportions with Yates continuity correction were used to examine the relationship between BPE suppression and pathologic complete response (pCR) in hormone receptor (HR)-positive and HR-negative cohorts. Results A total of 3528 MRI scans from 882 patients (mean age, 48 years ± 10 [standard deviation]) were reviewed and the subset of patients with high-quality BPE segmentation was determined (T1, 433 patients; T2, 396 patients; T3, 380 patients). In the HR-positive cohort, an association between lack of BPE suppression and lower pCR rate was detected at T2 (nonsuppressed vs suppressed, 11.8% [six of 51] vs 28.9% [50 of 173]; difference, 17.1% [95% CI: 4.7, 29.5]; P = .02) and T3 (nonsuppressed vs suppressed, 5.3% [two of 38] vs 27.4% [48 of 175]; difference, 22.2% [95% CI: 10.9, 33.5]; P = .003). In the HR-negative cohort, patients with nonsuppressed BPE had lower estimated pCR rate at all points, but the P values for the association were all greater than .05. Conclusions In hormone receptor-positive breast cancer, lack of background parenchymal enhancement suppression may indicate inferior treatment response. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Philpotts in this issue.

Purpose To determine if the change in tumor apparent diffusion coefficient (ADC) at diffusion-weighted (DW) MRI is predictive of pathologic complete response (pCR) to neoadjuvant chemotherapy for breast cancer. Materials and Methods In this prospective multicenter study, 272 consecutive women with breast cancer were enrolled at 10 institutions (from August 2012 to January 2015) and were randomized to treatment with 12 weekly doses of paclitaxel (with or without an experimental agent), followed by 12 weeks of treatment with four cycles of anthracycline. Each woman underwent breast DW MRI before treatment, at early treatment (3 weeks), at midtreatment (12 weeks), and after treatment. Percentage change in tumor ADC from that before treatment (ΔADC) was measured at each time point. Performance for predicting pCR was assessed by using the area under the receiver operating characteristic curve (AUC) for the overall cohort and according to tumor hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) disease subtype. Results The final analysis included 242 patients with evaluable serial imaging data, with a mean age of 48 years ± 10 (standard deviation); 99 patients had HR-positive (hereafter, HR+)/HER2-negative (hereafter, HER2-) disease, 77 patients had HR-/HER2- disease, 42 patients had HR+/HER2+ disease, and 24 patients had HR-/HER2+ disease. Eighty (33%) of 242 patients experienced pCR. Overall, ΔADC was moderately predictive of pCR at midtreatment/12 weeks (AUC = 0.60; 95% confidence interval [CI]: 0.52, 0.68; P = .017) and after treatment (AUC = 0.61; 95% CI: 0.52, 0.69; P = .013). Across the four disease subtypes, midtreatment ΔADC was predictive only for HR+/HER2- tumors (AUC = 0.76; 95% CI: 0.62, 0.89; P < .001). In a test subset, a model combining tumor subtype and midtreatment ΔADC improved predictive performance (AUC = 0.72; 95% CI: 0.61, 0.83) over ΔADC alone (AUC = 0.57; 95% CI: 0.44, 0.70; P = .032.). Conclusion After 12 weeks of therapy, change in breast tumor apparent diffusion coefficient at MRI predicts complete pathologic response to neoadjuvant chemotherapy. © RSNA, 2018 Online supplemental material is available for this article.

PurposeTo evaluate volumetric magnetic resonance (MR) imaging for predicting recurrence-free survival (RFS) after neoadjuvant chemotherapy (NACT) of breast cancer and to consider its predictive performance relative to pathologic complete response (PCR).Materials and methodsThis HIPAA-compliant prospective multicenter study was approved by institutional review boards with written informed consent. Women with breast tumors 3 cm or larger scheduled for NACT underwent dynamic contrast-enhanced MR imaging before treatment (examination 1), after one cycle (examination 2), midtherapy (examination 3), and before surgery (examination 4). Functional tumor volume (FTV), computed from MR images by using enhancement thresholds, and change from baseline (ΔFTV) were measured after one cycle and before surgery. Association of RFS with FTV was assessed by Cox regression and compared with association of RFS with PCR and residual cancer burden (RCB), while controlling for age, race, and hormone receptor (HR)/ human epidermal growth factor receptor type 2 (HER2) status. Predictive performance of models was evaluated by C statistics.ResultsFemale patients (n = 162) with FTV and RFS were included. At univariate analysis, FTV2, FTV4, and ΔFTV4 had significant association with RFS, as did HR/HER2 status and RCB class. PCR approached significance at univariate analysis and was not significant at multivariate analysis. At univariate analysis, FTV2 and RCB class had the strongest predictive performance (C statistic = 0.67; 95% confidence interval [CI]: 0.58, 0.76), greater than for FTV4 (0.64; 95% CI: 0.53, 0.74) and PCR (0.57; 95% CI: 0.39, 0.74). At multivariate analysis, a model with FTV2, ΔFTV2, RCB class, HR/HER2 status, age, and race had the highest C statistic (0.72; 95% CI: 0.60, 0.84).ConclusionBreast tumor FTV measured by MR imaging is a strong predictor of RFS, even in the presence of PCR and RCB class. Models combining MR imaging, histopathology, and breast cancer subtype demonstrated the strongest predictive performance in this study.

MRI has established value for defining extent of disease in the breast and is particularly helpful when ductal carcinoma in situ (DCIS) or multifocal or multicentric disease is present. The accuracy of MRI for measuring the extent of disease is influenced by a number of factors, including parameters of the image acquisition and contrast material administration methods, the histologic subtype of the tumor (ductal vs lobular) and the tumor’s hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) receptor status. When MRI is performed after neoadjuvant chemotherapy (NAC), its accuracy is lower, but it remains effective. After NAC, accuracy can also depend on the initial (pretreatment) tumor morphology and pattern of shrinkage, in addition to the imaging parameters and tumor subtype characteristics. When available, pretreatment MRI can facilitate the assessment of response and residual disease extent by focusing the evaluation to the original tumor bed. However, with or without preceding NAC, it has not yet been established that presurgical MRI leads to improved surgical outcomes or reductions in recurrence rates (1). A major benefit of neoadjuvant (vs adjuvant) systemic chemotherapy is greater possibility for breast conservation. Accurate presurgical assessment of residual disease extent at MRI can assist in making the decision for breast conservation versus mastectomy and inform the surgical approach. Toward that goal, many published studies have explored the accuracy of MRI for determining residual disease extent after NAC by comparing agreement between size measurements made at MRI and those made at postsurgical histopathologic examination. In two of the larger studies (2,3), agreement was higher in HR-negative/HER2-negative (triple-negative) and in HER2-positive subtypes, whereas it was lower in the HR-positive/HER2-negative subtype. A 2015 meta-analysis by Marinovich and colleagues (4) examined agreement between post-NAC MRI and pathologic tumor size in a pooled group of 300 patients. The performance of MRI was found to be generally superior to that of alternative tests (mammography, US, and clinical examination). There is special interest in understanding the ability of MRI to confirm a pathologic complete response (pCR) in the breast prior to surgery. A pCR is the most accepted surrogate end point for survival after neoadjuvant treatment of breast cancer. The U.S. Food and Drug Administration (FDA) considers pCR in support of accelerated drug approval for patients with high-risk, early-stage breast cancer (5). Recent improvements in chemotherapy regimens and targeted therapies for breast cancer have led to growing interest in identifying patients prior to surgery who have had exceptional responses and who may be candidates for de-escalated treatment (ie, reduction in the duration of NAC). In some cases, this may include omission of surgery (6). An ongoing multicenter clinical trial is assessing the accuracy of radiologic complete response on the basis of negative findings at three imaging modalities: mammography, US, and MRI (7). The trial uses image-directed biopsy to the tumor bed for assessing accuracy, and patients then proceed to surgery per the standard of care. A separate trial is also underway to test the feasibility of omitting surgery for patients with HER2-positive or triple-negative breast cancer who are deemed to be exceptional responders to NAC (8). Patients in this trial do not undergo surgery but proceed directly to radiation therapy. They are subsequently followed for ipsilateral breast recurrences every 6 months for 5 years by using a physical examination and mammography. In this trial, MRI is used instead of mammography at the discretion of the treating physician. The immediate goal of MRI after NAC is to provide information on the extent of residual disease in the breast, including both invasive and noninvasive components, to enable surgeons to obtain adequate surgical margins at initial surgery and avoid reexcision. There is also interest in understanding the ability of MRI to predict pCR, as defined for use as an intermediate end point for survival. As a surrogate end point, pCR is most commonly defined as no residual invasive disease in the breast or axilla. Stricter definitions require that neither residual invasive or noninvasive disease (ie, DCIS) remains. The 2014 FDA guidance allows either definition for pCR. Current MRI techniques cannot enable differentiation between invasive disease and DCIS, and mismatches can be expected if pCR is defined on the basis of invasive disease only. MRI also does not adequately evaluate the axilla; however, exclusion of axillary disease is required for a determination of pCR. MRI is not likely to be used alone to confirm pCR presurgically and may need to be used in combination with biopsy, particularly if omission of surgery is being considered. Appearing in this issue of Radiology, the article by Kim et al (9) is timely in revisiting the question of accuracy in estimating residual disease extent in light of the many issues discussed above. Similar to other recent reports, Kim et al found improved agreement between MRI and histopathologic findings when residual disease size was measured on delayed postinjection images—beyond the 90–120-second delay time that is generally recommended to balance diagnostic sensitivity and specificity. Kim and colleagues found that in the post-NAC setting, MRI led to underestimation of the total tumor size (invasive and DCIS) at 90 seconds after injection and overestimation of the tumor size at 360 and 590 seconds, the two delay times tested in the study. Greater discrepancies were found for cancers of lobular versus ductal histologic nature and for HR-positive/HER2-negative cancers versus other subtypes. The study by Kim et al has implications for the use of shortened or abbreviated breast MRI protocols that reduce the total postinjection imaging time. Results reported in this and other studies indicate that prolonged delay times result in better agreement with histopathologic estimates of total tumor size, and absence of late enhancement may be important for confirming pCR in the breast (10). Kim and colleagues found comparable agreement with histopathologic findings for the 360- and 590-second delay times, suggesting that there was no benefit to extending delay time beyond 360 seconds for measuring total tumor size in any breast cancer subtype. When tumor size was restricted to the invasive component only, no difference was found between the early and conventional delayed (360 seconds), early and late delayed (590 seconds), or the conventional and late delayed images. These results showed comparable results irrespective of delay, suggesting that for the task of predicting pCR, early postinjection timing may be sufficient and imaging times can be shortened. The findings of Kim et al suggest that separate guidelines may be needed for performing MRI to evaluate residual disease in the post-NAC setting. This may be especially needed if abbreviated MRI protocols are adopted. Further investigation of the effects of delay times shorter than 360 seconds may shed additional light on the need for separate protocols for treated and untreated breast cancers. It would be interesting for the authors to further explore this question in their data, which included imaging at 180-second delay. Imaging is likely to be the most effective method to assess response and guide treatment redirection noninvasively in the neoadjuvant setting. As more is learned about the biologic heterogeneity of breast cancer, MRI methods can be further refined for more effective use in personalized treatment strategies.

PURPOSE: To determine if the change in tumor apparent diffusion coefficient (ADC) at diffusion-weighted (DW) MRI is predictive of pathologic complete response (pCR) to neoadjuvant chemotherapy for breast cancer. MATERIALS AND METHODS: In this prospective multicenter study, 272 consecutive women with breast cancer were enrolled at 10 institutions (from August 2012 to January 2015) and were randomized to treatment with 12 weekly doses of paclitaxel (with or without an experimental agent), followed by 12 weeks of treatment with four cycles of anthracycline. Each woman underwent breast DW MRI before treatment, at early treatment (3 weeks), at midtreatment (12 weeks), and after treatment. Percentage change in tumor ADC from that before treatment (ΔADC) was measured at each time point. Performance for predicting pCR was assessed by using the area under the receiver operating characteristic curve (AUC) for the overall cohort and according to tumor hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) disease subtype. RESULTS: The final analysis included 242 patients with evaluable serial imaging data, with a mean age of 48 years ± 10 (standard deviation); 99 patients had HR-positive (hereafter, HR+)/HER2-negative (hereafter, HER2-) disease, 77 patients had HR-/HER2- disease, 42 patients had HR+/HER2+ disease, and 24 patients had HR-/HER2+ disease. Eighty (33%) of 242 patients experienced pCR. Overall, ΔADC was moderately predictive of pCR at midtreatment/12 weeks (AUC = 0.60; 95% confidence interval [CI]: 0.52, 0.68; P = .017) and after treatment (AUC = 0.61; 95% CI: 0.52, 0.69; P = .013). Across the four disease subtypes, midtreatment ΔADC was predictive only for HR+/HER2- tumors (AUC = 0.76; 95% CI: 0.62, 0.89; P < .001). In a test subset, a model combining tumor subtype and midtreatment ΔADC improved predictive performance (AUC = 0.72; 95% CI: 0.61, 0.83) over ΔADC alone (AUC = 0.57; 95% CI: 0.44, 0.70; P = .032.). CONCLUSION: After 12 weeks of therapy, change in breast tumor apparent diffusion coefficient at MRI predicts complete pathologic response to neoadjuvant chemotherapy. © RSNA, 2018 Online supplemental material is available for this article.

PurposeTo assess the relationship between parameters measured on dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging and fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) in primary invasive breast cancer.Materials and methodsThis HIPAA-compliant study was a retrospective review of medical records and therefore approved by the institutional review board without the requirement for informed consent. Patients with a diagnosis of invasive breast cancer from January 2005 through December 2009 who underwent both DCE MR imaging and FDG PET/CT before treatment initiation were retrospectively identified. Fractional volumes were measured for ranges of signal enhancement ratio (SER) values from DCE MR imaging data and compared with maximum standardized uptake values (SUVmax) from FDG PET/CT data. Linear regression analysis was performed to clarify the relationship between SER and SUVmax, adjusting for tumor size, pathologic grade, and receptor status.ResultsAnalyzed were 117 invasive breast cancers in 117 patients. Overall, a higher percentage of high washout kinetics was positively associated with SUVmax (1.57% increase in SUVmax per 1% increase in high washout; P = .020), and a higher percentage of low plateau kinetics was negatively associated with SUVmax (1.19% decrease in SUVmax per 1% increase in low plateau; P = .003). These relationships were strongest among triple-negative (TN) tumors (4.34% increase in SUVmax per 1% increase in high washout and 2.65% decrease in SUVmax per 1% increase in low plateau; P = .018 and .004, respectively).ConclusionIn invasive breast carcinoma, there is a positive relationship between the percentage of high washout and SUVmax and a negative relationship between the percentage of low plateau and SUVmax. These results are stronger in TN tumors.Supplemental materialhttp://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.13130058/-/DC1.

To prospectively determine the prevalence and predictive value of three-dimensional (3D) and dynamic breast magnetic resonance (MR) imaging and contrast material kinetic features alone and as part of predictive diagnostic models.The study protocol was approved by the institutional review board or ethics committees of all participating institutions, and informed consent was obtained from all participants. Although study data collection was performed before HIPAA went into effect, standards that would be compliant with HIPAA were adhered to. Data from the International Breast MR Consortium trial 6883 were used in the analysis. Women underwent 3D (minimum spatial resolution, 0.7 x 1.4 x 3 mm; minimal temporal resolution, 4 minutes) and dynamic two-dimensional (temporal resolution, 15 seconds) MR imaging examinations. Readers rated enhancement shape, enhancement distribution, border architecture, enhancement intensity, presence of rim enhancement or internal septations, and the shape of the contrast material kinetic curve. Regression was performed for each feature individually and after adjustment for associated mammographic findings. Multivariate models were also constructed from multiple architectural and dynamic features. Areas under the receiver operating characteristic curve (Az values) were estimated for all models.There were 995 lesions in 854 women (mean age, 53 years +/- 12 [standard deviation]; range, 18-80 years) for whom pathology data were available. The absence of enhancement was associated with an 88% negative predictive value for cancer. Qualitative characterization of the dynamic enhancement pattern was associated with an Az value of 0.66 across all lesion architectures. Focal mass margins (Az = 0.76) and signal intensity (Az = 0.70) were highly predictive imaging features. Multivariate models were constructed with an Az value of 0.880.Architectural and dynamic features are important in breast MR imaging interpretation. Multivariate models involving feature assessment have a diagnostic accuracy superior to that of qualitative characterization of the dynamic enhancement pattern.

To compare magnetic resonance (MR) imaging findings and clinical assessment for prediction of pathologic response to neoadjuvant chemotherapy (NACT) in patients with stage II or III breast cancer.The HIPAA-compliant protocol and the informed consent process were approved by the American College of Radiology Institutional Review Board and local-site institutional review boards. Women with invasive breast cancer of 3 cm or greater undergoing NACT with an anthracycline-based regimen, with or without a taxane, were enrolled between May 2002 and March 2006. MR imaging was performed before NACT (first examination), after one cycle of anthracyline-based treatment (second examination), between the anthracycline-based regimen and taxane (third examination), and after all chemotherapy and prior to surgery (fourth examination). MR imaging assessment included measurements of tumor longest diameter and volume and peak signal enhancement ratio. Clinical size was also recorded at each time point. Change in clinical and MR imaging predictor variables were compared for the ability to predict pathologic complete response (pCR) and residual cancer burden (RCB). Univariate and multivariate random-effects logistic regression models were used to characterize the ability of tumor response measurements to predict pathologic outcome, with area under the receiver operating characteristic curve (AUC) used as a summary statistic.Data in 216 women (age range, 26-68 years) with two or more imaging time points were analyzed. For prediction of both pCR and RCB, MR imaging size measurements were superior to clinical examination at all time points, with tumor volume change showing the greatest relative benefit at the second MR imaging examination. AUC differences between MR imaging volume and clinical size predictors at the early, mid-, and posttreatment time points, respectively, were 0.14, 0.09, and 0.02 for prediction of pCR and 0.09, 0.07, and 0.05 for prediction of RCB. In multivariate analysis, the AUC for predicting pCR at the second imaging examination increased from 0.70 for volume alone to 0.73 when all four predictor variables were used. Additional predictive value was gained with adjustments for age and race.MR imaging findings are a stronger predictor of pathologic response to NACT than clinical assessment, with the greatest advantage observed with the use of volumetric measurement of tumor response early in treatment.

To improve the quality of projection angiograms generated from three-dimensional magnetic resonance (MR) angiography data, the authors applied voxel shifting to create intermediate sections ("section doubling") prior to maximum intensity projection. To date, the authors have processed MR angiography studies with and without section doubling in 20 cases. Section doubling resulted in improved vessel contrast and delineation of continuity (especially of small vessels) in all cases.

To retrospectively evaluate high-spatial-resolution signal enhancement ratio (SER) imaging for the prediction of disease recurrence in patients with breast cancer who underwent preoperative magnetic resonance (MR) imaging.This retrospective study was approved by the institutional review board and was HIPAA compliant; informed consent was waived. From 1995 to 2002, gadolinium-enhanced MR imaging data were acquired with a three time point high-resolution method in women undergoing neoadjuvant therapy for invasive breast cancers. Forty-eight women (mean age, 49.1 years; range, 29.7-72.4 years) were divided into recurrence-free or recurrence groups. Volume measurements were tabulated for SER values between set ranges; cutoff criteria were defined to predict disease recurrence after surgery. Wilcoxon rank sum tests and the multivariate Cox proportional hazards regression model were used for evaluation.Breast tumor volume calculated from the number of voxels with SER values above a threshold corresponding to the upper limit of mean redistribution rate constant in benign tumors (0.88 minutes(-1)) and the volume of cancerous breast tissue infiltrating into the parenchyma were important predictors of disease recurrence. Seventy-five percent of patients with recurrence and 100% of deceased patients were identified as being at high risk for recurrence. Thirty percent of patients with recurrence and 67% of deceased patients were identified as having high risk before chemotherapy. No patients in the recurrence-free group were misidentified as likely to have recurrence. All three prechemotherapy parameters (total tumor volume, tumor volumes with high and low SER) and the postchemotherapy tumor volume with high SER were significantly different between the two groups. The multivariate Cox proportional hazards regression showed that, of the three prechemotherapy covariates, only the low SER and high SER tumor volumes (P = .017 and .049, respectively) were significant and independent predictors of tumor recurrence. Tumor volume with high SER was the only significant postchemotherapy covariate predictor (P = .038).High-spatial-resolution SER imaging may improve prediction for patients at high risk for disease recurrence and death.

The results of the study by Jiang et al suggest that diffuse optical spectroscopy may provide a sensitive method for detecting early biological changes in tumors that Forecast the likelihood of tumors to reach a complete response.

Radiology: Volume 266: Number 1—January 2013 n radiology.rsna.org 367 poor with the in-phase 2D T1-weighted images. Retrospectively going through our analysis, we found that we would have missed cast in one of the cases with use of 2D opposed-phase imaging instead of 3D fat-saturated imaging and vice versa in another case. In our experience, artifacts owing to high inflow have not hampered the diagnostic accuracy of the 2D images. In conclusion, we therefore suggest performing both sequences and using both for the detection of biliary cast.

Practical constraints make it difficult to build large-aperture echo-planar magnetic resonance (MR) imagers. The implementation of a pediatric imager and its performance are described. Spatial resolution and signal-to-noise levels comparable to those of 1982 state-of-the-art MR imagers have been achieved in imaging times of 0.05-0.15 seconds. T1 and T2 information are obtainable in the echo-planar mode. A major issue is that of chemical-shift displacements.

Theoretical analysis predicts that performing magnetic resonance (MR) imaging with partial (less than 90 degrees) flip angles can reduce imaging times two- to fourfold when lesions with elevated T1 values are being examined. This time savings occurs because repetition time (TR) is reduced when imaging is performed with partial flips. Partial flip MR imaging can also improve signal-to-noise ratio (S/N) in fast body imaging. For this study, analytical tools were used to predict image contrast and S/N for short TR, partial flip sequences. Experimental implementation of the short TR, partial flip sequences that analytical work had predicted would be optimal supported the analytical predictions and demonstrated their validity. Partial flip MR imaging is applicable to reducing imaging time only when the ratio of signal differences to noise exceeds threshold values in conventional MR images. Partial flip sequences can be used to advantage in MR imaging of both the head and the body, and the observed effects are predictable through theoretical analysis.

The response of different magnetic resonance (MR) techniques to tissue parameters - T1, T2, and N(H) - is a determinant of clinical efficacy. The large possible number of imaging techniques and range of variable parameters for each make it difficult to perform exhaustive evaluations in a single patient or even in animal models. In addition, changes in operating magnetic field strength change the relaxation times sufficiently so that the efficacy of a technique at a given field does not imply similar results at another field value. Tools are demonstrated that permit the evaluation of the efficacy of any model of response to tissue parameters, and also allow the investigation of the effects of changing magnetic field. Global maps of signal difference between tissues as well as calculated images are obtainable from a minimally sufficient data set. These tools serve as an important adjunct to experimental work.